Recent technological advances have made 3D ultrasound image acquisition practical in many cardiac and non-cardiac clinical settings, but its broad application is limited by difficulties in processing and analyzing the image data. One field in which 3D ultrasound has potential to make a valuable contribution is in assessing developmental dysplasia of the hip (DDH).
DDH is a condition affecting up to 3% of the population in which the acetabulum (the “socket” of the ball-and-socket hip joint) is poorly formed, resulting in a lax and unstable joint prone to premature osteoarthritis. About ⅓ of hip replacement surgeries in patients less than 60 years old are due to DDH. One of the main challenges in diagnosing DDH lies in defining the complex shape deformity of the acetabulum. The conventionally used Graf technique is based on calculating the bony angle (α) and cartilage angle (l) from 2D ultrasound images. However, this procedure has been criticized for high inter-observer and inter-scan variability. The cause of high inter-scan variance can be attributed to the mono-planar (2D) nature of the approach. Slight variations in the scanning angle can result in vastly different views of the hip joint which results in inconsistent measurement of the a angle.
Automatic segmentation of anatomic structures and lesions from medical ultrasound images is a formidable challenge in medical imaging due to image noise, blur and artifacts. There are multiple techniques for image segmentation in ultrasound. Several segmentation techniques have been applied at the hip joint. Hip segmentation is a tedious and time consuming process mainly due to its complex structure. Unsurprisingly, inter-observer and intra-observer variability are significant during manual segmentation. Several previous studies relied on CT imaging for the segmentation of the hip. For example, in one approach, an automatic segmentation was developed for pelvis and the femur for multi-slice CT data based on thresholds. This approach involved preprocessing steps such as Gaussian smoothing followed by histogram based thresholding. Morphological operations were then used to remove small objects and holes in the segmented image.
Although 3D ultrasound is a radiation-free alternative to CT for hip imaging, automatic techniques for hip joint segmentation are rare in 3D ultrasound. When compared to CT, ultrasound hip volumes contain artifacts such as speckle noise and acoustic shadowing which make it even more difficult to segment the acetabulum and the femoral head. Due to speckle noise, threshold based approaches cannot be extended reliably to ultrasound to date.